Average engagement rate is the fastest way to sanity check creator performance, but it only works if you compare it to the right benchmark and calculate it consistently. In this guide, you will learn what “good” looks like by platform and follower tier, how to compute engagement rate with clean formulas, and how to use the number in pricing, briefs, and reporting. Along the way, you will also see practical examples, decision rules, and a simple audit process you can run before you spend a dollar.
Average engagement rate: what it is and what it is not
Engagement rate is the share of an audience that actively interacts with a piece of content. In practice, “engagement” usually means likes, comments, shares, saves, and sometimes clicks, depending on the platform and what data you can access. The key point is that engagement rate is a ratio, so it helps you compare creators of different sizes. However, it is not a direct measure of sales impact, and it can be inflated by giveaways, controversy, or low quality traffic.
Before you benchmark anything, align on one definition inside your team. If you switch formulas between creators, you will rank them incorrectly. Also remember that engagement rate is content level, not creator level, unless you explicitly average it across a defined set of posts. As a rule, use at least 10 recent posts or 30 days of content when you can, otherwise one viral post will distort the picture.
- Takeaway: Decide your engagement definition and time window first – then benchmark.
- Takeaway: Treat a single post as a data point, not a verdict.
Key terms you need before you compare creators
Benchmarks only help when everyone speaks the same language. Here are the terms that most often get mixed up in influencer planning and reporting, plus how to apply them.
- Engagement rate (ER): Engagements divided by a denominator (followers, reach, or impressions). Use ER by reach when you can access reach.
- Reach: Unique accounts that saw the content. It is the cleanest denominator for ER because it reflects actual exposure.
- Impressions: Total views, including repeats. Use impressions when reach is unavailable, but expect lower ER values.
- CPM: Cost per thousand impressions. Formula: cost ÷ impressions × 1000. Use it to compare paid media efficiency to influencer content.
- CPV: Cost per view (common on TikTok and YouTube). Formula: cost ÷ views. Use it when video views are the primary KPI.
- CPA: Cost per acquisition (purchase, signup, install). Formula: cost ÷ conversions. Use it when you have tracking links or promo codes.
- Whitelisting: Brand runs ads through the creator’s handle (often called branded content ads). This changes pricing and usage rights.
- Usage rights: Permission to reuse creator content on brand channels or in ads, usually for a time period and specific placements.
- Exclusivity: A clause that prevents the creator from working with competitors for a set period. It should increase fees because it limits income.
For platform definitions, it helps to reference official documentation when you set reporting standards. For example, Meta explains how it counts reach and impressions across surfaces in its business help center: Meta Business Help Center.
How to calculate engagement rate (with formulas and examples)
There is no single universal formula, so you need to pick the one that matches your data access and goal. Below are the three most useful options, ordered from most reliable to most common.
1) Engagement rate by reach (best when available)
Formula: (likes + comments + shares + saves) ÷ reach × 100
Example: A Reel gets 2,400 likes, 110 comments, 220 shares, and 310 saves. Reach is 52,000. Total engagements are 3,040. ER by reach = 3,040 ÷ 52,000 × 100 = 5.85%.
- Use it when: You can get screenshots or creator analytics exports.
- Watch out for: Creators reporting reach for a different time window than engagements.
2) Engagement rate by impressions (good for view heavy formats)
Formula: (likes + comments + shares + saves) ÷ impressions × 100
Example: The same Reel has 78,000 impressions. ER by impressions = 3,040 ÷ 78,000 × 100 = 3.90%.
- Use it when: You are comparing content that gets repeat views.
- Decision rule: Do not compare ER by impressions to ER by reach in the same ranking.
3) Engagement rate by followers (most common, least precise)
Formula: (likes + comments + shares + saves) ÷ followers × 100
Example: Creator has 120,000 followers. ER by followers = 3,040 ÷ 120,000 × 100 = 2.53%.
- Use it when: You only have public data.
- Watch out for: Inflated follower counts from low quality growth will depress ER and hide real reach performance.
Engagement rate benchmarks by platform and follower tier
Benchmarks vary by platform because content distribution works differently. Short form video often reaches beyond followers, while feed posts can be more follower weighted. Use the table below as a starting point, then adjust based on niche and format. Importantly, treat these as ranges, not pass fail thresholds.
| Platform | Follower tier | Typical ER by followers | What “strong” often looks like | Notes for interpretation |
|---|---|---|---|---|
| 5k to 25k | 2.5% to 6% | 6% to 9% | Saves and shares matter more than likes for intent. | |
| 25k to 250k | 1.5% to 4% | 4% to 6% | Reels can outperform feed posts by reach. | |
| TikTok | 10k to 100k | 4% to 9% | 9% to 14% | Views and watch time often predict lift better than likes. |
| TikTok | 100k to 1M | 3% to 7% | 7% to 10% | Viral spikes are common – use medians, not averages. |
| YouTube | 10k to 100k | 1% to 4% | 4% to 6% | Comments and likes per view can be more stable than per sub. |
| YouTube | 100k to 1M | 0.8% to 3% | 3% to 5% | Long tail views can lower ER over time – set a measurement window. |
When you present benchmarks internally, explain the denominator. Otherwise, stakeholders will compare a TikTok ER by followers to an Instagram ER by reach and draw the wrong conclusion. If you need a quick education piece for your team, publish a short internal note and link to your process documentation. You can also build a reference hub by bookmarking practical posts from the InfluencerDB Blog and adding your own benchmark notes next to them.
Benchmarks by niche: why “good” depends on the audience
Niche changes engagement patterns because the audience behaves differently. Beauty audiences save tutorials, sports audiences comment during events, and B2B audiences click more than they like. That is why you should benchmark creators against peers in the same content category, not against the entire platform.
| Niche | Typical engagement signals | What to prioritize in reporting | Practical screening tip |
|---|---|---|---|
| Beauty and skincare | Saves, shares, before after comments | Saves per 1,000 reach | Check if comments mention shade, routine, or product questions. |
| Fitness | Shares, challenges, DMs, repeat viewers | Shares and completion rate | Look for consistent series content, not one off transformations. |
| Food | Saves, shares, recipe requests | Saves and link clicks | Ask for top performing posts by saves, not by likes. |
| Gaming | Comments, live chat, watch time | Average view duration | Scan comment quality – are people discussing gameplay or just emojis? |
| B2B and SaaS | Clicks, thoughtful comments, shares | CTR and qualified traffic | Use UTMs and judge by sessions and time on page, not likes. |
- Takeaway: Match your benchmark to the niche and the primary action you want – save, share, click, or watch.
A step by step framework to audit creators using engagement data
Once you have a benchmark range, you still need to decide whether a specific creator is worth the fee. Use this audit flow to move from “nice content” to a defensible decision. It is designed for teams that have a mix of public data and creator provided screenshots.
- Pick one denominator. If you can get reach, use ER by reach. If not, use ER by followers for everyone in the shortlist.
- Collect a consistent sample. Pull the last 10 to 20 posts in the same format you are buying (Reels vs feed, TikTok videos vs lives).
- Use medians, not just averages. A single viral post can double the mean. Median ER shows typical performance.
- Check engagement quality. Read 30 to 50 comments. Look for specific reactions, questions, and intent, not generic one word replies.
- Scan for volatility. If ER swings from 0.5% to 12% every other post, ask why. Format changes, giveaways, or boosted posts can explain it.
- Cross check audience fit. Ask for top audience countries, age brackets, and gender split when relevant. A high ER in the wrong market is still a miss.
- Flag risk signals. Sudden follower spikes, repetitive comments, and unusually high likes with low views can indicate low quality growth.
If you want a lightweight way to standardize this across campaigns, build a one page audit template and store it with your briefs. That way, the next time someone asks why you picked Creator A over Creator B, you can show the same criteria applied consistently.
How to use engagement benchmarks in pricing and negotiation
Engagement rate does not set price by itself, but it helps you negotiate with evidence. Start by translating performance into cost metrics that finance teams understand. Then you can decide whether to pay the rate, counter, or restructure deliverables.
Here is a practical way to do it:
- Step 1 – estimate impressions or reach. Use creator history. If they cannot share analytics, use a conservative assumption like 20% to 40% of followers reached for Instagram Reels, and validate later.
- Step 2 – compute an implied CPM. CPM = fee ÷ impressions × 1000. Compare it to your paid social CPMs for similar audiences.
- Step 3 – add value adjustments. Usage rights, exclusivity, category complexity, and production effort should increase price. On the other hand, weak audience fit or inconsistent performance should decrease it.
Example calculation: A creator quotes $2,500 for one TikTok. Their typical views are 80,000. Implied CPV is $2,500 ÷ 80,000 = $0.031. Implied CPM is $2,500 ÷ 80,000 × 1000 = $31.25. If your paid CPM for similar targeting is $18, you can counter by offering $1,500 to $2,000, or keep the fee but request usage rights for 30 days to justify the premium.
When you negotiate whitelisting, be explicit about duration and spend. A common structure is a base content fee plus a monthly whitelisting fee, because the creator’s handle becomes part of your ad performance. For disclosure and branded content rules, you can reference the FTC’s endorsement guidance: FTC endorsements and influencer guidance.
Common mistakes that make “average” benchmarks useless
Most benchmark decks fail because they mix apples and oranges. If you avoid the mistakes below, your engagement analysis will become a tool people trust instead of a number that gets debated in every meeting.
- Mixing formats: Reels, Stories, and feed posts behave differently. Benchmark each format separately.
- Using follower count as a proxy for reach: Followers do not equal exposure, especially on TikTok and Reels.
- Comparing different time windows: A post measured at 24 hours will not match one measured at 14 days.
- Ignoring comment quality: High engagement with low relevance can still fail to drive brand lift.
- Letting giveaways set expectations: Contest posts can inflate engagement and distort “normal” performance.
- Over weighting averages: Use medians and distribution checks so one viral outlier does not drive decisions.
Best practices: turning benchmarks into better briefs and better results
Once you know what average looks like, the next step is to use that knowledge to improve creative and measurement. The goal is not to chase a higher engagement rate at any cost. Instead, you want engagement that signals attention and intent, and you want reporting that connects content to outcomes.
- Set a benchmark range in the brief. Example: “Target ER by reach of 4% to 7% for Reels, measured at 7 days.” This sets expectations without forcing creators into gimmicks.
- Specify the engagement you value. If saves predict sales in your category, ask for tutorial style content and track saves per 1,000 reach.
- Require measurement artifacts. Ask for screenshots of reach, impressions, and interactions at a defined time stamp.
- Use UTMs and a clean naming convention. Even when you optimize for engagement, track clicks and conversions so you can learn what engagement actually correlates with revenue.
- Plan for iteration. Run two creative angles with the same creator and compare ER and downstream metrics before scaling.
If you need a repeatable workflow, keep a campaign playbook that includes your benchmark tables, formulas, and audit checklist. Updating it quarterly is usually enough, since platform distribution shifts over time. For additional practical templates and measurement ideas, browse the and adapt the sections that match your team’s reporting cadence.
A simple reporting template you can copy
To make engagement benchmarks actionable, your report should show context, not just a number. Use this structure for each creator and each deliverable. It keeps stakeholders focused on what happened, why it happened, and what you will do next.
- Inputs: deliverable type, posting date, fee, usage rights, exclusivity, whitelisting yes or no.
- Exposure: reach, impressions, views, watch time (if available).
- Engagement: likes, comments, shares, saves, clicks, ER by reach or impressions.
- Outcome: sessions, add to carts, purchases, signups, CPA (if tracked).
- Benchmark comparison: creator vs platform tier median, plus niche notes.
- Next action: scale, repeat with new angle, renegotiate, or drop.
Finally, keep your methodology visible. When someone asks “what is the average engagement rate,” you should be able to answer with a range, a denominator, and a measurement window. That clarity is what turns a benchmark into a decision tool.
